Facebook Research Scientist, Computer Vision (PhD) in Seattle, Washington
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Facebook's AR/VR organization has world-class researchers and engineers jointly working on building exciting products applying state of the art computational photography, computer vision, and machine learning methods as well as pushing the state of the art in these fields. The CoreAI group is looking for exceptional Computer Vision Research Scientist to join us in pushing forward the state of the art in scene reconstruction. In addition to working with researchers within the AR/VR organization, this role offers opportunities to collaborate closely with the Facebook AI research group and Facebook Reality Labs.
Working on highly efficient structure from motion algorithms to push the limits of computable scenes
Efficient dense scene reconstruction leveraging AI algorithms to advance the state of the art
Application of computational photography methods to real world problems including on mobile devices
Currently has or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the fields of Computer Vision, Computational Photography, or related field
Experience in one or more of the following areas: large-scale Structure from Motion, efficient camera registration, dense scene reconstruction, computational photography
2+ years of experience in geometric computer vision
2+ years of experience in camera tracking
2+ years of experience in C++, Python, or other language
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
Interpersonal experience: cross-group and cross-culture collaboration
Proven track record of achieving significant results as demonstrated by one or more of the following: grants, fellowships, patents, or first-authored publications at leading workshops or conferences such as CVPR, ECCV/ICCV, 3DV, SIGGRAPH, BMVC or similar.
Demonstrated software engineering experience via an internship, work experience, coding competitions, widely used contributions in open source repositories (e.g. GitHub), or contributions to collaborative code base research projects.
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